Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 72 (from 72) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*11:01:01-B*15:25-C*04:03-DRB1*15:01:01-DQB1*05:02:01-DPB1*02:01:02  China Yunnan Province Nu 2.6000107
 2  DRB1*16:01-DQB1*05:02-DPB1*02:01  Greece pop3 2.3000246
 3  DRB1*12:02:01-DQB1*05:02-DPB1*02:01:02  China Lijiang Naxi 1.8000100
 4  DQB1*05:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.5760496
 5  A*74:01:01-B*15:03:01-C*06:02:01-DRB1*16:02:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 6  DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 1.12011,064
 7  DRB1*14:01:01-DQB1*05:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.6610496
 8  DRB1*16:02:01-DQB1*05:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.5780496
 9  A*01:01:01-B*44:27:01-C*07:04:01-DRB1*16:01:01-DQA1*01:02:02-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 10  A*02:01:01-B*14:01:01-C*08:02:01-DRB1*07:01:01-DQA1*01:02:02-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 11  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*16:01:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.3891521
 12  A*02:01:01-B*37:01:01-C*07:04:01-DRB1*16:01:01-DQA1*01:02:02-DQB1*05:02-DPA1*02:06-DPB1*02:01:02  Russia Belgorod region 0.3268153
 13  A*03:01:01-B*35:01:01-C*02:02:02-DRB1*07:01:01-DQA1*02:01:01-DQB1*05:02-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 14  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*15:01:01-DQA1*01:01:01-DQB1*05:02-DPA1*01:03:01-DPB1*02:01  Russia Belgorod region 0.3268153
 15  A*03:01-B*07:02:01-C*04:01:01-DRB1*15:01:01-DQA1*01:01:01-DQB1*05:02-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 16  A*02:05:01-B*58:01:01-C*07:18:01-DRB1*16:01:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 17  A*25:01:01-B*18:01:01-C*03:03:01-DRB1*04:05:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 18  A*02:06-B*54:01-C*08:01-DRB1*08:03-DQA1*01:01-DQB1*05:02-DPB1*02:01  USA San Diego 0.2600496
 19  DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.23891,064
 20  A*74:03-B*51:01:01-C*15:02:01-DRB1*16:01-DQB1*05:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.231228,927
 21  A*68:02-B*49:01-C*07:27-DRB1*15:01-DQA1*01:02-DQB1*05:02-DPB1*02:01  Nicaragua Managua 0.2165339
 22  A*03:01-B*15:01-C*04:01-DRB1*15:06-DQA1*01:02-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.2101714
 23  A*03:01-B*35:01-C*04:01-DRB1*15:06-DQA1*01:02-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.2101714
 24  A*02:01:01-B*18:01:01-C*02:10:01-DRB1*11:01:02-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 25  A*02:02:01-B*15:03:01-C*02:10:01-DRB1*15:03:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 26  A*02:07:01-B*51:02:01-C*15:02:01-DRB1*14:54:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 27  A*11:01:01-B*55:01:01-C*03:03:01-DRB1*16:01:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 28  A*24:03:01-B*38:01:01-C*07:01:01-DRB1*13:05:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 29  DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.1936833
 30  A*02:02-B*07:02-C*03:04-DRB1*15:03-DQB1*05:02-DPB1*02:01  Panama 0.1900462
 31  A*23:01-B*35:08-C*04:01-DRB1*04:03-DQB1*05:02-DPB1*02:01  Panama 0.1900462
 32  DQA1*01:01-DQB1*05:02-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.18451,064
 33  A*11:01-B*56:01-C*04:01-DRB1*15:06-DQA1*01:02-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.1401714
 34  A*24:02-B*35:03-C*04:01-DRB1*15:01-DQA1*01:02-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.1401714
 35  DRB1*15:01-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.1384833
 36  DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.1200833
 37  A*02:01:01-B*51:01:01-C*16:02:01-DRB1*16:01-DQB1*05:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.114628,927
 38  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*16:01-DQB1*05:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.114028,927
 39  DRB1*15:01:01:01-DQB1*05:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.1010496
 40  A*02:01-B*18:01-C*07:01-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.07191,075
 41  A*11:01-B*15:25-C*01:02-DRB1*07:01-DQA1*02:01-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.0700714
 42  A*11:01-B*15:25-C*04:03-DRB1*15:01-DQA1*01:03-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.0700714
 43  A*24:02-B*38:02-C*07:02-DRB1*15:04-DQA1*01:02-DQB1*05:02-DPB1*02:01  Sri Lanka Colombo 0.0700714
 44  A*26:05-B*51:01-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 45  DRB1*15:02-DQA1*01:01-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.0680833
 46  DRB1*12:02-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.0600833
 47  DRB1*15:01-DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*02:01  China Zhejiang Han pop 2 0.0600833
 48  A*03:01-B*44:02-C*07:04-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05651,075
 49  A*32:01-B*27:05-C*02:02-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05651,075
 50  A*02:01-B*39:01-C*12:03-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05651,075
 51  A*23:01-B*44:02-C*07:04-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05651,075
 52  A*32:01-B*27:02-C*02:02-DRB1*16:02-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05641,075
 53  A*03:01-B*38:01-C*12:03-DRB1*16:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05641,075
 54  A*32:01-B*51:01-C*07:02-DRB1*14:01-DQB1*05:02-DPB1*02:01  Russia Karelia 0.05631,075
 55  DRB1*15:02-DQA1*01:01-DQB1*05:02-DPA1*02:02-DPB1*02:01  China Zhejiang Han pop 2 0.0520833
 56  DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.03971,064
 57  DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.03441,064
 58  A*03:01-B*44:02-C*07:04-DRB1*16:01-DQB1*05:02-DPB1*02:01  Germany DKMS - German donors 0.03293,456,066
 59  A*02:01-B*54:01-C*03:04-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 60  A*02:06-B*51:01-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 61  A*02:07-B*48:01-C*08:01-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 62  A*11:01-B*15:01-C*04:01-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 63  A*11:01-B*67:01-C*07:02-DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 64  A*24:02-B*07:02-C*07:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*02:01  Japan pop 17 0.03003,078
 65  A*24:02-B*15:01-C*08:01-DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 66  A*24:02-B*40:01-C*03:04-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 67  A*26:01-B*48:01-C*08:03-DRB1*14:07-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 68  A*26:03-B*51:01-C*14:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 69  A*31:01-B*51:02-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*02:01  Japan pop 17 0.03003,078
 70  A*02:01-B*44:02-C*07:04-DRB1*16:01-DQB1*05:02-DPB1*02:01  Germany DKMS - German donors 0.01473,456,066
 71  A*02:01-B*27:02-C*02:02-DRB1*16:01-DQB1*05:02-DPB1*02:01  Germany DKMS - German donors 0.01013,456,066
 72  DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*02:01  China Zhejiang Han pop 2 0.0056833

Notes:

* Haplotype Frequencies: Total number of copies of the haplotype in the population sample (Haplotypes / 2n) shown in percentages (%).
   Important: This field has been expanded to two decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
¹ Distribution - Shows the geographic distribution in overlaid maps of the complete haplotype (left icon) or the input alleles if low level resolution was entered (right icon).




   

Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools
Gonzalez-Galarza FF, McCabe A, Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, Del Cid-Pavon GM, Ramsbottom K, Ghattaoraya GS, Alfirevic A, Middleton D and Jones AR Nucleic Acid Research 2020, 48:D783-8.
Liverpool, U.K.

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